Diabetes is a chronic disease only controlled by constant vigilance. Chronic elevations, and likely fluctuations, of the blood glucose may result in long term complications (blindness, kidney failure, heart disease, and lower extremity amputations). Perversely, attempts at normalizing glucose concentrations also increases the risk of serious health issues related to hypoglycemia. Despite the use of insulin infusion pumps and programs that promote intensive diabetes management, the average Alc (an indicator of long-term blood glucose control) reported by major diabetes treatment centers remains higher than 8%, well above the recommended goal of 6.5-7%. Many factors contribute to this failure:    1) the difficulties in correctly estimating the amount of carbohydrates in a meal,    2) missed meal boluses, and    3) anxiety about anticipated hypoglycemia, resulting in patients giving themselves less insulin, especially overnight.
It has always been difficult to achieve compliance with complicated medical regimens, such as the administration of insulin three or more times a day. As long as diabetes treatment demands constant direct intervention, the vast majority of people with diabetes will not meet treatment goals. An expanding area of research addressing diabetes is working on developing automated closed loop systems that integrates glucose readings and insulin delivery without the on-going active intervention of the patient—an “artificial pancreas”.
We have developed an automated closed-loop system that contains a subcutaneous continuous glucose monitor and a subcutaneous insulin delivery pump for type 1 diabetes patients. These two components are connected by a control algorithm using data from the glucose sensor to determine the appropriate insulin delivery. We use a health monitoring system (HMS) algorithm that adds an independent safety layer to the overall system. The HMS analyzes CGM data and CGM trends in anticipation of impending hypoglycemia. The HMS issues electronic, visual and/or audio alerts in response to impending hypoglycemia (e.g. within 15 minutes), such as on the AP device screen, with a request for the investigator to intervene and treat the subject, e.g. with 16 g carbohydrate. A secondary alert may be sent as a text message, such as to the clinical team, that hypoglycemia is predicted and may also suggest taking outside action, such as eating carbohydrates, in order to prevent hypoglycemia.